Twitter Data Visualization using ggplot2

twitter_data_viz_barplot_tweet_activities_part_two.R

# Total tweets of 2019-05-28
ggplot(data.hour.date1)+
  geom_bar(aes(x = Hour,
               y = Total.Tweets,
               fill = I('red')),
           stat = 'identity',
           alpha = 0.75,
           show.legend = FALSE)+
  geom_hline(yintercept = mean(data.hour.date1$Total.Tweets),
             col = I('black'),
             size = 1)+
  geom_text(aes(fontface = 'italic',
                label = paste('Average:',
                              ceiling(mean(data.hour.date1$Total.Tweets)),
                              'Tweets per hour'),
                x = 6.5,
                y = mean(data.hour.date1$Total.Tweets)+5),
            hjust = 'left',
            size = 4)+
  labs(title = 'Total Tweets per Hours - Prabowo Subianto',
       subtitle = '28 May 2019',
       caption = 'Twitter Crawling 28 - 29 May 2019')+
  xlab('Time of Day')+
  ylab('Total Tweets')+
  ylim(c(0,100))+
  theme_bw()+
  scale_fill_brewer(palette = 'Dark2')

# Total tweets of 2019-05-29
ggplot(data.hour.date2)+
  geom_bar(aes(x = Hour,
               y = Total.Tweets,
               fill = I('red')),
           stat = 'identity',
           alpha = 0.75,
           show.legend = FALSE)+
  geom_hline(yintercept = mean(data.hour.date2$Total.Tweets),
             col = I('black'),
             size = 1)+
  geom_text(aes(fontface = 'italic',
                label = paste('Average:',
                              ceiling(mean(data.hour.date2$Total.Tweets)),
                              'Tweets per hour'),
                x = 1,
                y = mean(data.hour.date2$Total.Tweets)+6),
            hjust = 'left',
            size = 4)+
  labs(title = 'Total Tweets per Hours - Prabowo Subianto',
       subtitle = '29 May 2019',
       caption = 'Twitter Crawling 28 - 29 May 2019')+
  xlab('Time of Day')+
  ylab('Total Tweets')+
  ylim(c(0,100))+
  theme_bw()+
  scale_fill_brewer(palette = 'Dark2')